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The neuroscience study opens new avenues for understanding the brain’s role in learning and education. As researchers uncover more about the mechanisms underlying acquiring knowledge, educators can implement evidence-based strategies to enhance student outcomes. This blog post delves into the fascinating world of neuroscience, explores how the brain learns, and examines various learning theories and strategies informed by neuroscientific research.

Understanding the Basics of Neuroscience

Neuroscience refers to studying the nervous system, focusing on its role in behavior, cognition, and learning. The human brain, a complex organ, contains billions of neurons that transmit information through electrical and chemical signals. These neurons form networks, and the brain’s organization into different regions allows it to carry out specific functions.

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Language models can speed up and automate many tasks in areas such as text or code. What happens when they run themselves?

This new trend in generative AI is also called “self-prompting” or “auto-prompting”. The language model develops and executes prompts that can lead to new prompts based on an initial input.

This approach becomes truly powerful when combined with tools such as web search or the ability to test written code. The language model becomes an automatic assistant that can do much more than just generate text or code.

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New research from a team of scientists at the Cornell University Center for Bright Beams has made significant strides in developing new techniques to guide the growth of materials used in next-generation particle accelerators.

The study, published in the Journal of Physical Chemistry C, reveals the potential for greater control over the growth of superconducting Nb3Sn films, which could significantly reduce the cost and size of cryogenic infrastructure required for .

Superconducting accelerator facilities, such as those used for X-ray free-electron laser radiation, rely on niobium superconducting radio frequency (SRF) cavities to generate high-energy beams. However, the associated cryogenic infrastructure, energy consumption, and operating costs of niobium SRF cavities limit access to this technology.

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So if you’re going to make a xenobot, where do you start? Well, the Vermont team starts in a virtual Petri dish, on a computer, where an artificial intelligence (AI) program ‘evolves’ bunches of frog cells, based on their shape, to perform whatever task it is the scientists are interested in.

“It creates a population of virtual xenobots, deletes the ones that do a poor job and makes randomly modified copies of the survivors,” explains Bongard.

The scientists tell the AI how many rounds of this artificial selection process to complete and in just a few seconds, they have their design.

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(Visit: http://www.uctv.tv/)
1:39 — Understanding Primate Brain Development Using Stem Cell Systems — Rick Livesey.
18:58 — Human-Specific Genes and Neocortex Expansion in Development and Evolution — Wieland Huttner.
37:17 — Cellular and Molecular Features of Human Brain Expansion and Evolution — Arnold Kriegstein.

The human brain is one of, if not the most important factor that distinguishes our species from all others. Three experts explore the use of stem cells in understanding the primate brain, genes that guided the evolution of the human brain, and the features that enabled the expansion of human neural characteristics. Recorded on 09/29/2017. Series: “CARTA — Center for Academic Research and Training in Anthropogeny” [11/2017] [Show ID: 32927].

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